Abstract

The objective of this research is to develop a calendar variation model based on time series regression method for forecasting time series data with Ramadhan effect. In most Islamic countries, the trade activities frequently contain calendar variation pattern due to consumption to certain products usually follows lunar calendar, instead of the common solar calendar. This research focuses on the development of model building procedure to find the best calendar variation model. The proposed time series regression model uses dummy regression and/or autoregressive approach. Initially, this research focuses on the development of model building procedure to find the best calendar variation model. Then, this procedure is applied to modeling and forecasting of real time series data, specifically the monthly sales of Moslem boys’ clothes in Indonesia. The results show that the proposed model yields better forecast compared to the traditional decomposition method, seasonal ARIMA model, and Neural Networks.

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

calendar variation, lunar calendar, model building procedure, time series regression